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What We're Looking For :

- 8 - 14 years of experience in software engineering (backend or fullstack)
- 2 years of hands-on experience with LLMs (RAG, agents, prompt engineering)
- Strong experience building production-grade distributed systems
- Proficiency in Python
- Strong experience with SQL & NoSQL databases
- Hands-on experience with LangChain, LangGraph, or similar frameworks
- Experience deploying systems on AWS / Azure / GCP
- Robust understanding of APIs, microservices, and system design
- Experience with vector databases (Pinecone, Weaviate, FAISS, etc.)
- Familiarity with CI/CD pipelines and DevOps practices

Roles & Responsibilities :

- Develop and optimize LLM-based solutions : Lead the design and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
- Codebase ownership : Build and maintain/review high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL,



focusing on reusable components, scalability, and performance best practices.
- Cloud integration : Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
- Cross-functional collaboration : Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
- Mentoring and guidance : Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.

Good to Have :

- Exposure to frontend frameworks (React, Next.js) for fullstack roles
- Understanding of model evaluation, fine-tuning, or LLMOps
- Experience building multi-tenant or enterprise SaaS platforms

📌 Tanisha Systems - Principal Generative AI Engineer (India)
🏢 Tanisha Systems
📍 India